fsk119 commented on code in PR #27232:
URL: https://github.com/apache/flink/pull/27232#discussion_r2520771368
##########
docs/content.zh/docs/dev/table/sourcesSinks.md:
##########
@@ -191,20 +191,17 @@ Flink 会对工厂类逐个进行检查，确保其“标识符”是全局唯
#### Vector Search Table Source
-A `VectorSearchTableSource` searches an external storage system using an input
vector and returns the most similar top-K rows during runtime. Users
-can determine which algorithm to use to calculate the similarity between the
input data and data stored in the external system. In general, most
-vector databases support using Euclidean distance or Cosine distance to
calculate similarity.
+在运行期间, `VectorSearchTableSource` 会使用一个输入向量来搜索外部存储系统，并返回最相似的 Top-K
行。用户可以决定使用何种算法来计算输入数据与外部系统中存储的数据之间的相似度。总的来说，大多数向量数据库支持使用欧几里得距离（Euclidean
distance）或余弦距离（Cosine distance）来计算相似度。
-Compared to `ScanTableSource`, the source does not have to read the entire
table and can lazily fetch individual
-values from a (possibly continuously changing) external table when necessary.
+与 `ScanTableSource` 相比，该源无需读取整个表，并可以在需要时从一个(可能在持续变化的)外部表中惰性获取(lazily fetch)单个值。
-Compared to `ScanTableSource`, a `VectorSearchTableSource` currently only
supports emitting insert-only changes.
+与 `ScanTableSource` 相比，`VectorSearchTableSource` 目前仅支持 insert-only 数据流。
-Compared to `LookupTableSource`, a `VectorSearchTableSource` does not use
equality to determine whether a row matches.
+与 `LookupTableSource` 相比，`VectorSearchTableSource` 不会使用等值（equality）来判断行是否匹配。
-Further abilities are not supported. See the documentation of
`org.apache.flink.table.connector.source.VectorSearchTableSource` for more
information.
+目前不支持其他更进一步的功能。更多信息请参阅
`org.apache.flink.table.connector.source.VectorSearchTableSource` 的文档。
-The runtime implementation of a `VectorSearchTableSource` is a `TableFunction`
or `AsyncTableFunction`. The function will be called with the given vector
values during runtime.
+`VectorSearchTableSource` 的运行时实现是一个 `TableFunction` 或
`AsyncTableFunction`。在运行时，该函数会使用给定的向量值被调用。
Review Comment:
感觉不是很通顺？
```
在运行时，算子会根据给定的向量值调用该函数。
```
##########
docs/content.zh/docs/dev/table/sql/queries/vector-search.md:
##########
@@ -46,25 +44,25 @@ FROM input_table, LATERAL TABLE(VECTOR_SEARCH(
))
```
-### Parameters
+### 参数
-- `input_table`: The input table containing the data to be processed
-- `vector_table`: The name of external table that allows searching via vector
-- `vector_column`: The name of the column in the input table, its type should
be FLOAT ARRAY or DOUBLE ARRAY
-- `index_column`: A descriptor specifying which column from the vector table
should be used to compare the similarity with the input data
-- `top_k`: The number of top-k most similar rows to return
-- `config`: (Optional) A map of configuration options for the vector search
+* `input_table`: 包含待处理数据的输入表。
+* `vector_table`: 允许通过向量进行搜索的外部表的名称。
+* `vector_column`: 输入表中的列名，其类型应为 FLOAT ARRAY 或 DOUBLE ARRAY。
+* `index_column`: 一个描述符 (descriptor)，指定应使用向量表 (vector_table) 中的哪一列与输入数据进行相似度比较。
+* `top_k`: 要返回的 top-k 个最相似行的数量。
+* `config`: (可选) 用于向量搜索的配置选项 Map。
Review Comment:
用于向量搜索的配置选项 Map。-> 用于向量搜索的配置选项。
##########
docs/content.zh/docs/dev/table/sql/queries/vector-search.md:
##########
@@ -93,24 +91,23 @@ input_table, LATERAL TABLE(VECTOR_SEARCH(
CONFIG => MAP['async', 'true', 'timeout', '100s']
));
--- Searching with contant value
-SELECT *
-FROM TABLE(VECTOR_SEARCH(
+-- 使用常量值搜索
+SELECT * FROM TABLE(VECTOR_SEARCH(
TABLE vector_table,
ARRAY[10, 20],
DESCRIPTOR(index_column),
- 10,
+ 10
));
```
-### Output
+### 输出
-The output table contains all columns from the input table, the vector search
table columns and a column named `score` to indicate the similarity between the
input row and matched row.
+输出表包含输入表的所有列、向量搜索表 (vector search table) 的列，以及一个名为 `score`
的列，用于表示输入行与匹配行之间的相似度。
-### Notes
+### 注意事项
-1. The implementation of the vector table must implement interface
`org.apache.flink.table.connector.source.VectorSearchTableSource`. Please refer
to [Vector Search Table Source]({{< ref "/docs/dev/table/sourcesSinks"
>}}#vector-search-table-source) for details.
-2. `VECTOR_SEARCH` only supports to consume append-only tables.
-3. `VECTOR_SEARCH` does not require the `LATERAL` keyword when the function
call has no correlation with other tables. For example, if the search column is
a constant or literal value, `LATERAL` can be omitted.
+1. 向量表 (vector table) 的实现必须实现
`org.apache.flink.table.connector.source.VectorSearchTableSource` 接口。详情请参阅
[Vector Search Table Source]({{\< ref "/docs/dev/table/sourcesSinks"
\>}}\#vector-search-table-source)。
Review Comment:
The link is wrong here. Use
```
({{< ref "/docs/dev/table/sourcesSinks" >}}#vector-search-table-source)
```
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